DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
arxiv(2024)
Abstract
We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code
language model that achieves performance comparable to GPT4-Turbo in
code-specific tasks. Specifically, DeepSeek-Coder-V2 is further pre-trained
from an intermediate checkpoint of DeepSeek-V2 with additional 6 trillion
tokens. Through this continued pre-training, DeepSeek-Coder-V2 substantially
enhances the coding and mathematical reasoning capabilities of DeepSeek-V2,
while maintaining comparable performance in general language tasks. Compared to
DeepSeek-Coder-33B, DeepSeek-Coder-V2 demonstrates significant advancements in
various aspects of code-related tasks, as well as reasoning and general
capabilities. Additionally, DeepSeek-Coder-V2 expands its support for
programming languages from 86 to 338, while extending the context length from
16K to 128K. In standard benchmark evaluations, DeepSeek-Coder-V2 achieves
superior performance compared to closed-source models such as GPT4-Turbo,
Claude 3 Opus, and Gemini 1.5 Pro in coding and math benchmarks.
MoreTranslated text
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined